We rely on a semantic inverted index (we will refer to this index as LexI). This index maps sets of words to the
entities where these words appear.
LexI encodes the labels of all entities of the input ontologies \(\mathcal {O} _1\)  and \(\mathcal {O} _2\) , including their lexical variations (e.g., preferred labels, synonyms), in the form of key-value pairs
where the key is a set of words and the value is a set of entities
such that the set of words of the key
appears in (one of) the entity labels.
Similar indexes are commonly used in information retrieval applications [1]}, Entity Resolution systems [2]}, and also exploited in ontology alignment systems (e.g., LogMap [3]}, ServOMap [4]}
and AML [5]}) to reduce the search space and enhance the matching process.
Table REF  shows a few example entries of LexI for two input ontologies.
